研究者詳細 - 森江　隆

論文 - 森江　隆

分割表示315 件中 41 - 60 件目／全件表示 >>

A VLSI Spiking Neural Network with Symmetric STDP and Associative Memory Operation 査読有り

F. Maldonado H., H. Tanaka, T. Matsuo, T. Morie, K. Aihara

18th Int. Conf. on Neural Information Processing (ICONIP2011) III ( 7064 ) 381 - 388 2011年11月

知的画像認識技術と脳型LSI実装招待有り査読有り

森江隆, 石川聖二

電子情報通信学会誌 94 ( 6 ) 459 - 463 2011年06月

アナログ・デジタル融合方式LSI技術による脳型視覚システム招待有り査読有り

森江隆

IEICE Fundamentals Review 1 ( 1 ) 19 - 29 2007年07月

A Hippocampus-Inspired Environment-Specific Knowledge Acquisition System Utilizing Common Knowledge with Contextual Information 査読有り国際誌

Akinobu Mizutani, Yuichiro Tanaka, Hakaru Tamukoh, Osamu Nomura, Katsumi Tateno, Takashi Morie

International Joint Conference on Neural Networks (IJCNN 2024) 2024年06月

CMOS Digital-Analog Mixed Signal VLSI Implementation of a Hippocampus-Inspired Model 査読有り国際誌

Yuka Shishido, Osamu Nomura, Katsumi Tateno, Hakaru Tamukoh, Takashi Morie

International Joint Conference on Neural Networks (IJCNN 2024) 2024年06月

Enhancing Memory Capacity of Reservoir Computing with Delayed Input and Efficient Hardware Implementation with Shift Registers 査読有り国際誌

Soshi Hirayae, Kanta Yoshioka, Atsuki Yokota, Ichiro Kawashima, Yuichro Tanaka, Yuichi Katori, Osamu Nomura, Takashi Morie, Hakaru Tamukoh

International Symposium on Circuits and Systems (ISCAS 2024) 2024年05月

Learning reservoir dynamics with temporal self-modulation 査読有り国際誌

Sakemi Y., Nobukawa S., Matsuki T., Morie T., Aihara K.

Communications Physics 7 ( 29 ) 1 - 11 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Reservoir computing (RC) can efficiently process time-series data by mapping the input signal into a high-dimensional space via randomly connected recurrent neural networks (RNNs), which are referred to as a reservoir. The high-dimensional representation of time-series data in the reservoir simplifies subsequent learning tasks. Although this simple architecture allows fast learning and facile physical implementation, the learning performance is inferior to that of other state-of-the-art RNN models. In this study, to improve the learning ability of RC, we propose self-modulated RC (SM-RC) that extends RC by adding a self-modulation mechanism. SM-RC can perform attention tasks where input information is retained or discarded depending on the input signal. We find that a chaotic state can emerge as a result of learning in SM-RC. Furthermore, we demonstrate that SM-RC outperforms RC in NARMA and Lorenz model tasks. Because the SM-RC architecture only requires two additional gates, it is physically implementable as RC, thereby providing a direction for realizing edge artificial intelligence.

DOI： 10.1038/s42005-023-01500-w

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85182165175&origin=inward

Robust Binary Encoding for Ternary Neural Networks Toward Deployment on Emerging Memory 査読有り国際誌

Ninnart Fuengfusin, Hakaru Tamukoh, Osamu Nomura, Takashi Morie

International Joint Conference on Neural Networks (IJCNN 2024) 2024年06月

FPGA Implementation of a Chaotic Boltzmann Machine Annealer 査読有り国際誌

K. Yoshioka, Y. Katori, Y. Tanaka, O. Nomura, T. Morie

International Joint Conference on Neural Networks (IJCNN 2023) 2023年06月

Efficient Repetition Coding for Deep Learning Towards Implementation Using Emerging Non-volatile Memory with Write-errors 査読有り国際誌

N. Fuengfusin, H. Tamukoh, Y. Tanaka, O. Nomura, T. Morie

International Joint Conference on Neural Networks (IJCNN 2023) 2023年06月

Random Network Structure of Materials Developing Next Generation AI Devices for Autonomous Robotics 招待有り国際誌

H. Tanaka, H. Tamukoh, T. Morie

239th ECS Meeting with the 18th International Meeting on Chemical Sensors (IMCS) 2021年06月

A hardware intelligent processing accelerator for domestic service robots 査読有り

Y. Ishida, T. Morie, H. Tamukoh

Advanced Robotics 2020年07月

Initial states and analog switching behaviors of two major tantalum oxide resistive memories 査読有り国際誌

Li Y., Tsurumaki-Fukuchi A., Arita M., Morie T., Takahashi Y.

Japanese Journal of Applied Physics 59 ( 4 ) 2020年04月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2020 The Japan Society of Applied Physics. A systematic study was performed to understand the two major operation modes, valence change memory (VCM) and electrochemical memory (ECM), of tantalum oxide resistive memory, which were categorized by the type of conductive filament. The tantalum oxide insulator layer was predictably fabricated to modify the pristine oxygen-vacancy concentration in the insulator layer, where tantalum and copper top electrodes were used to achieve VCM and ECM modes. The distinguishable characteristics of the initial state and analog resistive switching operation revealed the prerequisites for switching capabilities and demonstrated the effects of oxygen vacancies in the two switching modes.

DOI： 10.35848/1347-4065/ab8022

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85083310643&origin=inward

Reconstructing bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems 査読有り

Itoh Y., Uenohara S., Adachi M., Morie T., Aihara K.

Chaos 30 ( 1 ) 2020年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2020 Author(s). Bifurcation-diagram reconstruction estimates various attractors of a system without observing all of them but only from observing several attractors with different parameter values. Therefore, the bifurcation-diagram reconstruction can be used to investigate how attractors change with the parameter values, especially for real-world engineering and physical systems for which only a limited number of attractors can be observed. Although bifurcation diagrams of various systems have been reconstructed from time-series data generated in numerical experiments, the systems that have been targeted for reconstructing bifurcation diagrams from time series measured from physical phenomena so far have only been continuous-time dynamical systems. In this paper, we reconstruct bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems with different parameter values. The generated time-series datasets are perturbed by dynamical noise and contaminated by observational noise. To reconstruct the bifurcation diagrams only from the time-series datasets, we use an extreme learning machine as a time-series predictor because it has a good generalization property. Hereby, we expect that the bifurcation-diagram reconstruction with the extreme learning machine is robust against dynamical noise and observational noise. For quantitatively verifying the robustness, the Lyapunov exponents of the reconstructed bifurcation diagrams are compared with those of the bifurcation diagrams generated in numerical experiments and by the electronic circuits.

DOI： 10.1063/1.5119187

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078467746&origin=inward

超立方体上の疑似ビリヤードダイナミクスに基づくレザバー計算のFPGA実装

山本大智, 川島一郎, 田向権, 森江隆, 香取勇一

人工知能学会全国大会論文集 ( 一般社団法人人工知能学会 ) 2020 ( 0 ) 3Rin422 - 3Rin422 2020年01月

記述言語：日本語掲載種別：研究論文（その他学術会議資料等）

<p>レザバー計算(RC)はリカレントニューラルネットワーク(RNN)の枠組みの1つで，時系列データの処理を目的に応用されている．機械学習モデルに対して，ディジタル回路実装を行うことで高速な演算速度を省電力で実現することが期待できる．香取らはディジタル回路との親和性が高いレザバー計算モデルを提案した．しかし，香取らのモデルをField Programmable Gate Array(FPGA)のようなディジタル回路に実装する場合，ニューロン数の変更に大きな制限が発生する．小規模な回路実装を行う手法として川嶋らがカオスボルツマンマシンのディジタル回路実装に用いたハードウェア指向アルゴリズムを提案している．本研究では川嶋らの提案したハードウェア指向アルゴリズムを基に対象のレザバー計算モデルを改良することで，ディジタル回路実装における回路リソースの消費を軽減可能なモデルを構築した．また，本研究のハードウェア指向アルゴリズムにより、レザバー計算の高速化の実現、人工知能構築のための新しいプラットフォームの確立が期待される．</p>

DOI： 10.11517/pjsai.JSAI2020.0_3Rin422

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130007857093

Hippocampus Model for Episodic Memory Processing Using Associative Memory 査読有り

立野勝巳, 森江隆

The proceedings of NOLTA2020 - 138 2020年01月

Prediction of Sensory Information and Generation of Motor Commands for Autonomous Mobile Robots Using Reservoir Computing 査読有り国際誌

M. Inada, Y. Tanaka, H. Tamukoh, K. Tateno, T. Morie, Y. Katori

Proc. of the 2019 Int. Symp. on Nonlinear Theory and its Applications (NOLTA2015) 2019年12月

脳型人工知能技術の開発招待有り

石井信, 岡田真人, 菅生康子, 大羽成征, 山崎匡, 森江隆, 國吉康夫

人工知能 2019年11月

Switching current of Ta<inf>2</inf>O<inf>5</inf>-based resistive analog memories 査読有り

Li Y., Tsurumaki-Fukuchi A., Arita M., Morie T., Takahashi Y.

2019 Silicon Nanoelectronics Workshop, SNW 2019 2019年06月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2019 JSAP. Multilevel switching (MS) behaviors in Ta2O5-based resistive random-access-memory (ReRAM) have been drawing attentions as hardware artificial synapse. However, operating resistances, which decide the power consumption of whole system, are relatively low for future integration. In this work, we investigated the characteristics of two kinds of ReRAMs operating with different mechanisms; Cu-top-electrode and Ta-top-electrode Ta2O5-based ReRAMs. By taking account of resistance of high resistive state (HRS), we clarify the difference of MS characteristics between the two kinds of ReRAM devices.

DOI： 10.23919/SNW.2019.8782931

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070868210&origin=inward

社会実装を目指したホームサービスロボットの研究開発

小野智寛, 坂田拓馬, 吉井拓巳, 上村大地, 金丸和樹, 中村健太郎, 西村雄太, 森江隆, 田向権, 堀三晟, 石田裕太郎, 田中悠一朗, 吉元裕真, 阿部佑志, 武藤冬樹, 椛島康平, 福宿将士

ロボティクス・メカトロニクス講演会講演概要集 ( 一般社団法人日本機械学会 ) 2019 ( 0 ) 1P2 - I02 2019年01月

記述言語：日本語掲載種別：研究論文（その他学術会議資料等）

<p>Home service robots have begun attracting attention due to decreasing birthrate and increasing aging population. We,"Hibikino-Musashi@Home"team, develop home service robots, and participate international competitions; RoboCup@Home and World Robot Challenge (WRC), which are established to realize that robots will work and live with people in domestic environments. In this paper, we introduce our robots and technologies, especially an object recognition and manipulation system. We use You Only Look Once (YOLO) for object recognition. To train YOLO, a big dataset which is difficult to prepare in a short term is required. For this, we develop an automatic annotation system for YOLO which can generate 1.7 million training data, and we can complete training of YOLO in a day. To grasp objects, estimation of object orientations is required. Our system can detect the orientations by processing point clouds of objects. By using the system, we obtained about 30% of scores in Tidy Up Task in the WRC.</p>

DOI： 10.1299/jsmermd.2019.1P2-I02

CiNii Article

その他リンク： https://ci.nii.ac.jp/naid/130007774525

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